深度学习环境搭建部署(DeepLearning 神经网络)

工作环境

显卡:GPU
系统:Ubuntu 16.04.5 LTS
cuda:10.0
Python:3.x

1. 创建conda环境

官网下载地址:https://www.anaconda.com/distribution/#download-section

下载合适的安装文件,然后运行。

1 cd init
2 sudo wget https://repo.anaconda.com/archive/Anaconda3-2019.03-MacOSX-x86_64.pkg
3 bash Anaconda3-2019.03-Linux-x86_64.sh

根据提示操作,并选择安装目录,默认安装在~/anaconda3/ 目录下。

注:初始化操作

1、如果默认不初始化,则安装之后,没有conda命令,需要手动初始化

installation finished.
Do you wish the installer to initialize Anaconda3
by running conda init? [yes|no]
[no] >>>

 
 

You have chosen to not have conda modify your shell scripts at all.
To activate conda's base environment in your current shell session:

 
 

eval "$(/home/cortex/anaconda3/bin/conda shell.YOUR_SHELL_NAME hook)"

 
 

To install conda's shell functions for easier access, first activate, then:

 
 

conda init

 
 

If you'd prefer that conda's base environment not be activated on startup,
set the auto_activate_base parameter to false:

 
 

conda config --set auto_activate_base false

 
 

Thank you for installing Anaconda3!

 
 

===========================================================================

 
 

Anaconda and JetBrains are working together to bring you Anaconda-powered
environments tightly integrated in the PyCharm IDE.

 
 

PyCharm for Anaconda is available at:
https://www.anaconda.com/pycharm

 
  
 
2、如果选择初始化,则会修改~/.bashrc文件,并创建conda命令

installation finished. Do you wish the installer to initialize Anaconda3 by running conda init
? [yes|no] "deeplearning" 105L, 3558C written installation finished. Do you wish the installer to initialize Anaconda3 by running conda init? [yes|no] [no] >>> yes WARNING: The conda.compat module is deprecated and will be removed in a future release. no change /home/cortex/anaconda3/condabin/conda no change /home/cortex/anaconda3/bin/conda no change /home/cortex/anaconda3/bin/conda-env no change /home/cortex/anaconda3/bin/activate no change /home/cortex/anaconda3/bin/deactivate no change /home/cortex/anaconda3/etc/profile.d/conda.sh no change /home/cortex/anaconda3/etc/fish/conf.d/conda.fish no change /home/cortex/anaconda3/shell/condabin/Conda.psm1 no change /home/cortex/anaconda3/shell/condabin/conda-hook.ps1 no change /home/cortex/anaconda3/lib/python3.7/site-packages/xonsh/conda.xsh no change /home/cortex/anaconda3/etc/profile.d/conda.csh modified /home/cortex/.bashrc ==> For changes to take effect, close and re-open your current shell. <== If you'd prefer that conda's base environment not be activated on startup, set the auto_activate_base parameter to false: conda config --set auto_activate_base false Thank you for installing Anaconda3! =========================================================================== Anaconda and JetBrains are working together to bring you Anaconda-powered environments tightly integrated in the PyCharm IDE. PyCharm for Anaconda is available at: https://www.anaconda.com/pycharm

退出conda环境

1 conda deactivate

2. 进入conda py3.6

1 conda create -n py36 python=3.6
2 conda activate py36


3. 安装必要包
#修改清华的pip源

1 mkdir ~/.pip
2 touch ~/.pip/pip.conf

#pip.conf中写入以下内容

[global]
index-url = https://pypi.tuna.tsinghua.edu.cn/simple

安装包

1 pip install numpy==1.16.2
2 pip install opencv-python==4.1.0.25
3 pip install keras==2.1.4
4 pip install tensorflow-gpu==1.13.1


4. 安装nccl2

下载地址:https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html

根据系统和cuda版本下载对应的nccl2

1 sudo dpkg -i nccl-repo-ubuntu1604-2.4.7-ga-cuda10.0_1-1_amd64.deb
2 sudo apt-key add /var/nccl-repo-2.4.7-ga-cuda10.0/7fa2af80.pub(根据提示执行)
3 sudo apt update
4 sudo apt install libnccl2=2.4.7-1+cuda10.0 libnccl-dev=2.4.7-1+cuda10.0

5. 安装openmpi

下载地址:https://www.open-mpi.org/faq/?category=building#easy-build

1 sudo wget https://download.open-mpi.org/release/open-mpi/v4.0/openmpi-4.0.1.tar.gz
2 gunzip -c openmpi-4.0.1.tar.gz | tar xf -
3 cd openmpi-4.0.1/
4 sudo ./configure --prefix=/usr/local
5 sudo make all install

6. 安装horovod

文档说明:https://github.com/horovod/horovod/blob/master/docs/gpus.md

1 HOROVOD_GPU_ALLREDUCE=NCCL pip install --no-cache-dir horovod

安装过程中可能出现的问题:

1、ImportError: libcudnn.so.7: cannot open shared object file: No such file or directory

根据版本,下载对应的文件:https://developer.nvidia.com/rdp/cudnn-download

1 sudo dpkg -i libcudnn7_7.6.0.64-1+cuda10.0_amd64.deb
2 sudo dpkg -i libcudnn7-dev_7.6.0.64-1+cuda10.0_amd64.deb

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